DEVELOPING AN ACTUALISTIC STROMATOLITE FACIES MODEL: EXAMPLE FROM THE PALEOPROTEROZOIC

One of the goals of microbialite studies is to clearly understand the environmental constraints of their formation to inform facies models. The hypersaline, intertidal embayment of Hamelin Pool (W. Australia) dominated uniformitarian facies models for decades and relegated stromatolites to that unique environment for billions of years into the rock record. The channels of Eluethra and the Exumas, Bahamas extended the analog into the subtidal zone. Lacustrine and fluvial stromatolites provided additional facies possibilities, often associated with unique non-marine biota and evaporites.

The use of the modern analog decreases with deep time. Archean-Mesoproterozoic stromatolites are finer grained and dominated by cement fabrics. Macrostructural forms are more varied and include branching columns and complex fascicles. Therefore, in order to develop a facies model that incorporates stromatolite form—from macro- down to the microstructural attributes—an actualistic approach is necessary.

We investigated a Paleoproterozoic stromatolite bed (Biwabik Iron Formation, MN) using cores and supplemented the data with field studies. The stratigraphy and local sedimentary structures support a shallow marine environment. However, unique attributes are not analogous to the common carbonate ramps and banks of the Phanerozoic. Stromatolites are associated with a bimodal sediment population of coated grains and allochthonous greenalite peloids. Sedimentary structures include meter-scale channels, gutter casts, flat-pebble conglomerate, and cross-bedded oolite. Unique features include complex breccia and poorly-sorted pisolite. Stromatolites are finely laminated and resemble geyserite. To develop an actualistic facies model, we created cm-scale lithofacies logs for 4 closely spaced cores (< 2 km apart). To predict vertical and lateral transitions between cores, we utilized reservoir modeling software (Petrel) to compare a deterministic facies model approach to a less biased stochastic method that honors proportions of lithofacies using statistical rules based on a pre-defined 3-D training image of a simple depositional setting. The stochastic method provided several competing resolutions that fit modern peritidal facies models and therefore challenge our simplistic view of marine settings.